<p dir="ltr">The goal of this dissertation is to develop precision technologies to facilitate establishing, in the context of stochastic organismal dynamics, organizational principles that govern basic regulatory processes in living systems. We focus on biological timekeeping, the interplay of biological lengths and timescales, and strategies governing the control of rapid vs. precise adaptation to changing phenomena supporting complex phenotypes. In particular, individual cells of unicellular organisms respond with remarkable precision and plasticity in their growth and division to changes in their noisy environments. Cells rely on scalable timekeepers and quantitative tradeoffs to accomplish this precision. In this dissertation we will address longstanding open questions in cell biology, such as: How does an individual cell maintain size homeostasis across multigenerational dynamics, as it repeatedly grows and divides? How does an organism adapt its growth rate to reflect changing environmental conditions? The development of understanding of systems-level organizational principles in a controlled experimental system in turn advances our general ability to predict and control stochastic organismal dynamics, and thus develop functional synthetic adaptive systems.</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/25664454 |
| Date | 23 April 2024 |
| Creators | Karl Ferdinand Ziegler (18421836) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/PRECISION_TECHNOLOGIES_FOR_LONG-TERM_IMAGING_OF_STOCHASTIC_ORGANISMAL_DYNAMICS/25664454 |
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